Compensated Box-Jenkins transfer function for short term load forecast
- Oklahoma Univ., Norman, OK (United States). School of Electrical Engineering and Computer Science
In the past years, the Box-Jenkins ARIMA method and the Box-Jenkins transfer function method (BJTF) have been among the most commonly used methods for short term electrical load forecasting. But when there exists a sudden change in the temperature, both methods tend to exhibit larger errors in the forecast. This paper demonstrates that the load forecasting errors resulting from either the BJ ARIMA model or the BJTF model are not simply white noise, but rather well-patterned noise, and the patterns in the noise can be used to improve the forecasts. Thus a compensated Box-Jenkins transfer method (CBJTF) is proposed to improve the accuracy of the load prediction. Some case studies have been made which result in about a 14-33% reduction of the root mean square (RMS) errors of the forecasts, depending on the compensation time period as well as the compensation method used.
- OSTI ID:
- 7116900
- Report Number(s):
- CONF-920432--
- Journal Information:
- Proceedings of the American Power Conference; (United States), Journal Name: Proceedings of the American Power Conference; (United States) Vol. 54:2; ISSN PAPWA; ISSN 0097-2126
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
240100* -- Power Systems-- (1990-)
29 ENERGY PLANNING, POLICY, AND ECONOMY
290100 -- Energy Planning & Policy-- Energy Analysis & Modeling
292000 -- Energy Planning & Policy-- Supply
Demand & Forecasting
296000 -- Energy Planning & Policy-- Electric Power
CALCULATION METHODS
ELECTRIC POWER INDUSTRY
ENERGY MODELS
FORECASTING
FUNCTIONS
INDUSTRY
LOAD MANAGEMENT
MANAGEMENT
NOISE
PERFORMANCE TESTING
PLANNING
POWER SYSTEMS
RELIABILITY
TESTING
TRANSFER FUNCTIONS